P1294: SINGLE-CELL RNA SEQUENCING REVEALS TUMOR CELL HETEROGENEITY AND COMPREHENSIVE IMMUNE PROFILE OF T FOLLICULAR HELPER CELL LYMPHOMA
Authors: S. Suma, M. Fujisawa, Y. Abe, Y. Suehara, D. Kaji, T. Sugio, K. Kato, K. Akashi, K. Matsue, N. Nakamura, A. Suzuki, Y. Suzuki, S. Chiba, M. Sakata-Yanagimoto
Journal: HemaSphere (2022)

Background: Angioimmunoblastic T-cell lymphoma (AITL) and other nodal lymphomas of T follicular helper (TFH) cell origin (TFH lymphoma) are associated with immune dysregulation. However, comprehensive immune profiles of TFH lymphoma have not been fully investigated. The RHOA G17V mutation (G17V) is found in 60-70% of TFH lymphoma and considered to gain a novel function through binding to VAV1 protein. Nevertheless, the prevalence of homozygous (Homo) and heterozygous (Hetero) G17V mutations and the difference in their oncogenicity due to its zygosity remain unclear. Aims: We performed single-cell RNA sequencing (scRNA-seq) for immune and tumor cells of TFH lymphoma to determine (1) the specific immune profiles, (2) the characteristics of tumor cells and (3) the mechanisms of clonal evolution from G17V Hetero to Homo. Methods: We collected 29 PB (12 at initial diagnosis [ID], 17 at relapsed/refractory diagnosis [RR]) and 10 LN (6 ID, 4 RR) from 25 patients with TFH lymphoma, 7 homeostatic LN (HLN) from patients with solid cancers. scRNA-seq and single-cell T cell receptor (TCR) sequencing were performed by the Chromium system (10x Genomics) from 16 PB and 9 LN of TFH lymphoma patients and 7 HLN. Publically available scRNA-seq data from 5 healthy donors (HD) were also integrated as controls. scRNA-seq data analysis was performed by Seurat, Scater and Batchelor for quality control, integration, and clustering; SingleR for annotation; Monocle3 and Slingshot for trajectory analysis; Immunarch for TCR repertoire analysis; gene set variation analysis (GSVA) for pathway analysis. VarTrix pipeline was used to detect mutation distribution in scRNA-seq data. Results: In total, 98,891 cells from PB and 68,738 cells from LN were analyzed. Unsupervised clustering identified 19 T/NK-, 2 B-, and 9 myeloid-cell clusters in PB (Figure 1). Tumor cells were identified by the expanded TCR clonality and the TFH-like gene expression signatures. (1) Subsequent clustering and GSVA of each cell type identified dysfunctional CD8 T cells (Dys CD8) in PB and LN of patients, some of which had enriched the proliferation signature (Pro CD8) (Figure 2). In some samples, Dys/Pro CD8 shared their TCRs between PB and LN, suggested that they have the same cellular origin. The proportion of Pro CD8 in LN correlated with that of TREG in PB; moreover, TREG effector function was activated in both PB and LN of patients compared to HD and HLN, respectively. By sub-clustering of myeloid subset, C1QA/B/C (C1Q) + macrophages and LAMP3+PD-L1+ dendritic cells (DCs) increased in LN of RR patients, whereas C1Q+ monocytes increased and CLEC9A+ conventional DCs and plasmacytoid DCs decreased in PB. (2) Differential expression gene (DEG) analysis identified five tumor-specific gene candidates and the cell surface protein PLS3 was validated by flow cytometry (Figure 3). (3) The G17V RHOA-mutated cells were detected in 6 PB and 3 LN. The G17V Hetero- versus Homo-mutated cells were 657 vs 59 in PB, while 1529 vs 288 in LN. DEG and GSVA in LN identified that the regulatory signature was significantly activated in Homo, whereas the proliferation signature was up-regulated in Hetero (Figure 4). Image:Summary/Conclusion: These results clarified the comprehensive immune structures including novel tumor-specific markers in TFH lymphoma. PLS3, one of the new tumor markers, could be detected by flow cytometry, a viable method in clinical practice. In the clonal evolution process from the G17V Hetero to Homo, the proliferative signaling switch to the immune escape signaling.